In this article
In Tamil Nadu a business inbox receives three languages, not two: English, Tamil in Tamil script, and Tanglish — Tamil written in English letters. The same customer may switch between all three in one conversation.
Most automation handles only English, which means a large share of messages fall to the fallback and look like the business does not understand its own customers.
The three forms, and why they matter
Form | Example | Who uses it |
English | “What is the price?” | Younger, urban, professional contexts |
Tamil script | “விலை என்ன?” | Comfortable Tamil typists, often older or rural |
Tanglish | “price enna?” / “evlo rate?” | The most common in casual business chat |
Tanglish is the one businesses forget to build for, and it is frequently the largest group.
Build keyword rules in all three
For each common question, add variants:
Intent | English | Tamil | Tanglish |
Price | price, cost, rate, how much | விலை, ரேட் | evlo, enna rate, rate enna, prize |
Location | address, location, where | முகவரி, எங்கே | enga, address enga, idam |
Timing | time, open, hours | நேரம், திறந்து | eppo open, timing enna |
Available | available, stock, in stock | இருக்கா, கிடைக்குமா | iruka, kedaikuma, stock iruka |
Booking | book, appointment, slot | புக், நேரம் | book panna, slot iruka |
Delivery | delivery, shipping | டெலிவரி | delivery iruka, anupuveengala |
Add the common misspellings too: “prize” for price, “adress”, “availabe”. People type fast on phones.
Export your fallback messages weekly and read them; that is where you find the real phrasings your customers use. See our chatbot metrics guide.
Detect and set the language
Rather than guessing every time:
1. Ask once, at the start: “Tamil-la pesalaama or English? Reply 1 for தமிழ், 2 for English”
2. Store the answer against the contact
3. Use that language for all future automated messages to them
4. Allow switching: “Reply TAMIL or ENGLISH to change”
Setting it once and remembering it is better than detecting it per message, which gets confused by Tanglish.
Write templates in pairs
Every automated message needs a version in each language. Not a literal translation: an adaptation.
English
Hi! Thanks for messaging [Business] 👋 1 — Prices 2 — Location & timing 3 — Book an appointment 4 — Talk to our team
Tanglish
Hi! [Business]-ku welcome 🙏 1 — Rate list 2 — Address & timing 3 — Appointment book panna 4 — Team kitta pesa
Tamil
வணக்கம்! [Business]-க்கு வரவேற்கிறோம் 🙏 1 — விலை விவரம் 2 — முகவரி மற்றும் நேரம் 3 — நேரம் பதிவு செய்ய 4 — எங்கள் குழுவுடன் பேச
Which to use as your Tamil default depends on your audience. For most consumer businesses in Tamil Nadu, Tanglish reads as more natural and friendly than formal literary Tamil, which can feel stiff.
Have a native speaker write these. Machine-translated Tamil is recognisable and makes a business look careless.
Route to the right person
• Tag each contact with their language
• Route Tamil conversations to Tamil-speaking staff
• Show the language tag in the inbox, so whoever opens it knows
• Note it in the contact record for phone follow-ups too
See our shared team inbox guide.
Where AI helps and where it does not
AI models handle Tamil and Tanglish better than keyword rules, because they cope with phrasing you never anticipated. That is genuinely useful for the long tail.
Limits to respect:
• Accuracy in Tamil and especially Tanglish is lower than in English; test with your own customers’ actual messages before trusting it
• Keep prices, addresses, policies and anything that must be exactly right in keyword rules, in both languages
• Make sure the handover message and the fallback exist in both languages
• Review AI conversations in Tamil weekly for the first month; errors in a language the reviewer does not read go unnoticed
See our keyword vs AI guide and AI agents guide.
Tone differs, not just words
• Tamil conversation tends to be warmer and more personal; a blunt translated English line can read as curt
• வணக்கம் and 🙏 land well in Tamil, where “Hi” alone can feel cold
• Forms of address matter: “ungaluku” rather than “unaku” with customers
• Keep product names, brand names and technical terms in English where that is how customers say them; forcing pure Tamil reads as artificial
Beyond Tamil
The same approach applies if you serve Hindi, Malayalam, Telugu or Kannada speakers: ask once, store the preference, build templates and rules per language, and route to someone who speaks it.
Do not add a language you cannot actually support. A Hindi auto-reply followed by an English-only human is worse than English throughout.
Measure
Metric | Why |
Conversations by language | Who your customers actually are |
Fallback rate per language | Usually far higher in Tamil; that is your gap |
Response time by language | Whether Tamil customers wait longer |
Conversion rate by language | Whether you serve one group better |
AI accuracy in Tamil | Before relying on it |
If Tamil conversations convert worse than English ones, the problem is your coverage, not your customers.
Frequently asked questions
Should the default be Tamil or English? Whichever most of your customers use. For local consumer businesses in Tamil Nadu, Tamil or Tanglish as default often works better than the usual reverse.
Can I just machine translate my English templates? Have a native speaker review them at minimum. Machine-translated Tamil marketing copy reads badly.
Do I need Tamil script, or is Tanglish enough? Build both. Many customers type in Tamil script even when they read Tanglish comfortably.
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